BUS 733 Week 6 Performance and Measurement Example

Measuring a Transformation That Takes a Decade: A Balanced Scorecard for a Rural Energy Cooperative

[Student Name]

University of Phoenix

BUS/733: Transforming the Business

Week 6 Assignment

[Instructor Name]

[Date]

Great Plains Energy Cooperative and all measures, targets and results are composites written for a model paper.

Great Plains Energy Cooperative, which supplies wholesale power to 22 member cooperatives in Kansas and Nebraska, is three years into a ten-year plan to replace coal with wind, solar, storage and flexible gas. Previous weeks established the vision, analyzed the environment and resources, planned the leadership of a plant closure and set sustainability goals. The board now asks a practical question: how will it know, year by year, whether the transformation is on track? Final outcomes such as lower emissions and stable rates arrive late, so a transformation needs measures that warn of trouble while there is still time to act.

Current Measures

Monthly board reports cover wholesale rates, operating margin, outage frequency and duration, safety incidents and plant availability. These are useful for running the current business but say little about the new one. None measures progress on forecasting, storage operations, retraining, interconnection or member programs, so the board learns about delays only when projects slip.

The Balanced Scorecard

Kaplan and Norton (1996) argued that the balanced scorecard should serve as a management system, not just a set of measures. Leaders translate the vision into objectives, communicate them, link them to plans and budgets and use feedback to learn and adjust strategy. The standard version groups objectives under four headings: money, the people the firm serves, the work it does well and the skills and systems it must grow.

Adapting the Perspectives

For a member-owned cooperative, the customer perspective becomes the member perspective, and the financial perspective centers on affordability and financial strength rather than profit. Because sustainability is central to this transformation, Great Plains adds a fifth perspective for environmental and community outcomes.

Strategy Map

The map runs from the bottom up. People and capabilities, such as retrained workers and forecasting skills, drive operational excellence in integrating renewables and storage. Operational excellence drives reliability and member satisfaction, along with lower emissions. Those, in turn, support stable rates and financial strength. Each arrow is a hypothesis that measurement can test.

Why Transformations Need Different Measures

Routine performance systems assume a stable strategy. A transformation changes what the organization does, so measures built for the old model can mislead. Plant availability, for example, will fall as coal units approach retirement and run less often, which is planned and healthy, yet a board trained to watch availability may read it as failure. Conversely, rising wind output might look like success even if curtailment is wasting much of it. Measures must be rebuilt around the new strategy, and some legacy measures should be retired or reinterpreted alongside the plants they once tracked.

Financial Measures

Wholesale rate growth relative to inflation, debt service coverage, the cost per megawatt-hour of new generation compared with plan and stranded cost from retired coal assets.

Member Measures

Member cooperative satisfaction from an annual survey, participation in efficiency and demand response programs and reliability in the worst weather week of each year.

Operational Measures

Day-ahead wind and solar forecast error, battery availability, interconnection milestones met on time, share of energy from wind and solar and curtailment rates.

People Measures

Share of coal plant workers enrolled in or completing retraining, retention of critical skills before retirement dates, safety incident rate during transition and employee trust in leadership from pulse surveys.

Sustainability Measures

Carbon emissions compared with the 2025 baseline, water withdrawals, community transition fund commitments and the number of host county jobs preserved through site reuse.

Leading and Lagging Indicators

Lagging indicators include emissions, rates and satisfaction. Leading indicators include forecast accuracy, training completion, interconnection milestones and early participation in member programs. If leading indicators weaken, leaders can act before lagging results decline.

Do the Measures Predict Outcomes

Ittner and Larcker (1998) studied whether customer satisfaction measures predicted later financial results and found that they did in some settings, but the relationship was not uniform and had limits at very high satisfaction levels. Ittner and Larcker (2003) later reported that few firms they surveyed had checked whether their chosen nonfinancial indicators actually moved results, and they urged firms to build causal models and check them with data. Great Plains will treat each link in its strategy map as a hypothesis and test it as data accumulate. For example, it will check whether better forecast accuracy actually reduces balancing costs and whether retraining completion predicts retention.

Targets

Targets carry dates and owners. Forecast error will fall below 8% day-ahead by 2028. Retraining enrollment will reach 85% of eligible workers by 2027. Wholesale rates will stay within 2% per year of inflation. Emissions will fall 50% by 2030.

Risks in Measurement

Measures can be gamed. A plant team might report high retraining enrollment while few complete the courses, so the cooperative will measure completion and job placement. Too many measures dilute attention, so the scorecard is limited to about 20. Some measures, such as trust, are imprecise and should be read as trends.

A Sample Quarter

In the third quarter of the plan's third year, the dashboard showed forecast error at 11%, above the path to the 8% target, while battery availability was strong at 97%. Retraining enrollment reached 78%, but completion lagged at 52% because evening classes conflicted with plant shifts. Rates stayed within target, and emissions were 31% below baseline. The executive team responded by adding a second forecasting vendor for comparison and moving classes to paid work hours. The example shows how leading indicators prompt specific actions months before lagging results would reveal a problem.

Owners and Data

Each measure has an executive owner responsible for data quality and action plans. A small analytics team will build a single dashboard drawing from operations, finance and human resources systems.

Review Rhythm

The executive team will review leading indicators monthly. The board will review the full scorecard quarterly, with one meeting each year devoted to testing strategy map links and updating targets. Kaplan and Norton (2008) recommended separating operational reviews from strategy reviews so that urgent issues do not crowd out learning, and Great Plains will follow that practice.

Linking Measures to Incentives

Executive incentives will include a mix of financial, reliability, people and emissions measures, weighted so that no single measure dominates. This reduces the temptation to hit one target at the expense of others.

Learning and Adjustment

When measures show that an assumption is wrong, the plan should change. If storage performs better than expected, the cooperative might accelerate it. If retraining fails to retain workers, it might redesign the program. Measurement serves learning, not only accountability.

Research Questions

The case suggests examining which leading indicators best predict transformation outcomes in regulated utilities and how cooperatives balance member and financial measures.

Conclusion

Great Plains needs measures that show progress on a decade-long transformation before final outcomes arrive. A balanced scorecard with five perspectives, a strategy map, leading and lagging indicators, tested links, owners, targets and a review rhythm gives the board early signals and a basis for adjusting the plan.

References

Ittner, C. D., & Larcker, D. F. (1998). Are nonfinancial measures leading indicators of financial performance? An analysis of customer satisfaction. Journal of Accounting Research, 36, 1-35. https://doi.org/10.2307/2491304

Ittner, C. D., & Larcker, D. F. (2003). Coming up short on nonfinancial performance measurement. Harvard Business Review, 81(11), 88-95.

Kaplan, R. S., & Norton, D. P. (1996). Using the balanced scorecard as a strategic management system. Harvard Business Review, 74(1), 75-85.

Kaplan, R. S., & Norton, D. P. (2008). Mastering the management system. Harvard Business Review, 86(1), 62-77.